Move methods for outputting from Suggest.

Bug: 8844931
Change-Id: I83dde6c37b75ed1e1ae4e0972e169d30ada8faf5
This commit is contained in:
Keisuke Kuroyanagi 2013-12-18 16:47:23 +09:00
parent 9ee9095528
commit d8f35f7b4c
6 changed files with 317 additions and 282 deletions

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@ -31,6 +31,7 @@ LATIN_IME_CORE_SRC_FILES := \
digraph_utils.cpp \
error_type_utils.cpp \
multi_bigram_map.cpp \
suggestions_output_utils.cpp \
unigram_property.cpp) \
$(addprefix suggest/core/layout/, \
additional_proximity_chars.cpp \

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@ -1,64 +0,0 @@
/*
* Copyright (C) 2012 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef LATINIME_SHORTCUT_UTILS
#define LATINIME_SHORTCUT_UTILS
#include "defines.h"
#include "suggest/core/dicnode/dic_node_utils.h"
#include "suggest/core/dictionary/binary_dictionary_shortcut_iterator.h"
namespace latinime {
class ShortcutUtils {
public:
static int outputShortcuts(BinaryDictionaryShortcutIterator *const shortcutIt,
int outputWordIndex, const int finalScore, int *const outputCodePoints,
int *const frequencies, int *const outputTypes, const bool sameAsTyped) {
int shortcutTarget[MAX_WORD_LENGTH];
while (shortcutIt->hasNextShortcutTarget() && outputWordIndex < MAX_RESULTS) {
bool isWhilelist;
int shortcutTargetStringLength;
shortcutIt->nextShortcutTarget(MAX_WORD_LENGTH, shortcutTarget,
&shortcutTargetStringLength, &isWhilelist);
int shortcutScore;
int kind;
if (isWhilelist && sameAsTyped) {
shortcutScore = S_INT_MAX;
kind = Dictionary::KIND_WHITELIST;
} else {
// shortcut entry's score == its base entry's score - 1
shortcutScore = finalScore;
// Protection against int underflow
shortcutScore = max(S_INT_MIN + 1, shortcutScore) - 1;
kind = Dictionary::KIND_SHORTCUT;
}
outputTypes[outputWordIndex] = kind;
frequencies[outputWordIndex] = shortcutScore;
frequencies[outputWordIndex] = max(S_INT_MIN + 1, shortcutScore) - 1;
const int startIndex2 = outputWordIndex * MAX_WORD_LENGTH;
DicNodeUtils::appendTwoWords(0, 0, shortcutTarget, shortcutTargetStringLength,
&outputCodePoints[startIndex2]);
++outputWordIndex;
}
return outputWordIndex;
}
private:
DISALLOW_IMPLICIT_CONSTRUCTORS(ShortcutUtils);
};
} // namespace latinime
#endif // LATINIME_SHORTCUT_UTILS

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@ -0,0 +1,261 @@
/*
* Copyright (C) 2013 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "suggest/core/dictionary/suggestions_output_utils.h"
#include "suggest/core/dicnode/dic_node.h"
#include "suggest/core/dicnode/dic_node_utils.h"
#include "suggest/core/dictionary/dictionary.h"
#include "suggest/core/dictionary/binary_dictionary_shortcut_iterator.h"
#include "suggest/core/policy/scoring.h"
#include "suggest/core/session/dic_traverse_session.h"
namespace latinime {
const int SuggestionsOutputUtils::MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT = 16;
// TODO: Split this method.
/* static */ int SuggestionsOutputUtils::outputSuggestions(
const Scoring *const scoringPolicy, DicTraverseSession *traverseSession,
int *frequencies, int *outputCodePoints, int *outputIndicesToPartialCommit,
int *outputTypes, int *outputAutoCommitFirstWordConfidence) {
#if DEBUG_EVALUATE_MOST_PROBABLE_STRING
const int terminalSize = 0;
#else
const int terminalSize = min(MAX_RESULTS,
static_cast<int>(traverseSession->getDicTraverseCache()->terminalSize()));
#endif
DicNode terminals[MAX_RESULTS]; // Avoiding non-POD variable length array
for (int index = terminalSize - 1; index >= 0; --index) {
traverseSession->getDicTraverseCache()->popTerminal(&terminals[index]);
}
const float languageWeight = scoringPolicy->getAdjustedLanguageWeight(
traverseSession, terminals, terminalSize);
int outputWordIndex = 0;
// Insert most probable word at index == 0 as long as there is one terminal at least
const bool hasMostProbableString =
scoringPolicy->getMostProbableString(traverseSession, terminalSize, languageWeight,
&outputCodePoints[0], &outputTypes[0], &frequencies[0]);
if (hasMostProbableString) {
outputIndicesToPartialCommit[outputWordIndex] = NOT_AN_INDEX;
++outputWordIndex;
}
// Initial value of the loop index for terminal nodes (words)
int doubleLetterTerminalIndex = -1;
DoubleLetterLevel doubleLetterLevel = NOT_A_DOUBLE_LETTER;
scoringPolicy->searchWordWithDoubleLetter(terminals, terminalSize,
&doubleLetterTerminalIndex, &doubleLetterLevel);
int maxScore = S_INT_MIN;
// Force autocorrection for obvious long multi-word suggestions when the top suggestion is
// a long multiple words suggestion.
// TODO: Implement a smarter auto-commit method for handling multi-word suggestions.
// traverseSession->isPartiallyCommited() always returns false because we never auto partial
// commit for now.
const bool forceCommitMultiWords = (terminalSize > 0) ?
scoringPolicy->autoCorrectsToMultiWordSuggestionIfTop()
&& (traverseSession->isPartiallyCommited()
|| (traverseSession->getInputSize()
>= MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT
&& terminals[0].hasMultipleWords())) : false;
// TODO: have partial commit work even with multiple pointers.
const bool outputSecondWordFirstLetterInputIndex =
traverseSession->isOnlyOnePointerUsed(0 /* pointerId */);
if (terminalSize > 0) {
// If we have no suggestions, don't write this
outputAutoCommitFirstWordConfidence[0] =
computeFirstWordConfidence(&terminals[0]);
}
// Output suggestion results here
for (int terminalIndex = 0; terminalIndex < terminalSize && outputWordIndex < MAX_RESULTS;
++terminalIndex) {
DicNode *terminalDicNode = &terminals[terminalIndex];
if (DEBUG_GEO_FULL) {
terminalDicNode->dump("OUT:");
}
const float doubleLetterCost = scoringPolicy->getDoubleLetterDemotionDistanceCost(
terminalIndex, doubleLetterTerminalIndex, doubleLetterLevel);
const float compoundDistance = terminalDicNode->getCompoundDistance(languageWeight)
+ doubleLetterCost;
const bool isPossiblyOffensiveWord =
traverseSession->getDictionaryStructurePolicy()->getProbability(
terminalDicNode->getProbability(), NOT_A_PROBABILITY) <= 0;
const bool isExactMatch = terminalDicNode->isExactMatch();
const bool isFirstCharUppercase = terminalDicNode->isFirstCharUppercase();
// Heuristic: We exclude freq=0 first-char-uppercase words from exact match.
// (e.g. "AMD" and "and")
const bool isSafeExactMatch = isExactMatch
&& !(isPossiblyOffensiveWord && isFirstCharUppercase);
const int outputTypeFlags =
(isPossiblyOffensiveWord ? Dictionary::KIND_FLAG_POSSIBLY_OFFENSIVE : 0)
| (isSafeExactMatch ? Dictionary::KIND_FLAG_EXACT_MATCH : 0);
// Entries that are blacklisted or do not represent a word should not be output.
const bool isValidWord = !terminalDicNode->isBlacklistedOrNotAWord();
// Increase output score of top typing suggestion to ensure autocorrection.
// TODO: Better integration with java side autocorrection logic.
const int finalScore = scoringPolicy->calculateFinalScore(
compoundDistance, traverseSession->getInputSize(),
terminalDicNode->isExactMatch()
|| (forceCommitMultiWords && terminalDicNode->hasMultipleWords())
|| (isValidWord && scoringPolicy->doesAutoCorrectValidWord()));
if (maxScore < finalScore && isValidWord) {
maxScore = finalScore;
}
// Don't output invalid words. However, we still need to submit their shortcuts if any.
if (isValidWord) {
outputTypes[outputWordIndex] = Dictionary::KIND_CORRECTION | outputTypeFlags;
frequencies[outputWordIndex] = finalScore;
if (outputSecondWordFirstLetterInputIndex) {
outputIndicesToPartialCommit[outputWordIndex] =
terminalDicNode->getSecondWordFirstInputIndex(
traverseSession->getProximityInfoState(0));
} else {
outputIndicesToPartialCommit[outputWordIndex] = NOT_AN_INDEX;
}
// Populate the outputChars array with the suggested word.
const int startIndex = outputWordIndex * MAX_WORD_LENGTH;
terminalDicNode->outputResult(&outputCodePoints[startIndex]);
++outputWordIndex;
}
if (!terminalDicNode->hasMultipleWords()) {
BinaryDictionaryShortcutIterator shortcutIt(
traverseSession->getDictionaryStructurePolicy()->getShortcutsStructurePolicy(),
traverseSession->getDictionaryStructurePolicy()
->getShortcutPositionOfPtNode(terminalDicNode->getPtNodePos()));
// Shortcut is not supported for multiple words suggestions.
// TODO: Check shortcuts during traversal for multiple words suggestions.
const bool sameAsTyped = scoringPolicy->sameAsTyped(traverseSession, terminalDicNode);
const int shortcutBaseScore = scoringPolicy->doesAutoCorrectValidWord() ?
scoringPolicy->calculateFinalScore(compoundDistance,
traverseSession->getInputSize(), true /* forceCommit */) : finalScore;
const int updatedOutputWordIndex = outputShortcuts(&shortcutIt,
outputWordIndex, shortcutBaseScore, outputCodePoints, frequencies, outputTypes,
sameAsTyped);
const int secondWordFirstInputIndex = terminalDicNode->getSecondWordFirstInputIndex(
traverseSession->getProximityInfoState(0));
for (int i = outputWordIndex; i < updatedOutputWordIndex; ++i) {
if (outputSecondWordFirstLetterInputIndex) {
outputIndicesToPartialCommit[i] = secondWordFirstInputIndex;
} else {
outputIndicesToPartialCommit[i] = NOT_AN_INDEX;
}
}
outputWordIndex = updatedOutputWordIndex;
}
DicNode::managedDelete(terminalDicNode);
}
if (hasMostProbableString) {
scoringPolicy->safetyNetForMostProbableString(terminalSize, maxScore,
&outputCodePoints[0], &frequencies[0]);
}
return outputWordIndex;
}
/* static */ int SuggestionsOutputUtils::computeFirstWordConfidence(
const DicNode *const terminalDicNode) {
// Get the number of spaces in the first suggestion
const int spaceCount = terminalDicNode->getTotalNodeSpaceCount();
// Get the number of characters in the first suggestion
const int length = terminalDicNode->getTotalNodeCodePointCount();
// Get the distance for the first word of the suggestion
const float distance = terminalDicNode->getNormalizedCompoundDistanceAfterFirstWord();
// Arbitrarily, we give a score whose useful values range from 0 to 1,000,000.
// 1,000,000 will be the cutoff to auto-commit. It's fine if the number is under 0 or
// above 1,000,000 : under 0 just means it's very bad to commit, and above 1,000,000 means
// we are very confident.
// Expected space count is 1 ~ 5
static const int MIN_EXPECTED_SPACE_COUNT = 1;
static const int MAX_EXPECTED_SPACE_COUNT = 5;
// Expected length is about 4 ~ 30
static const int MIN_EXPECTED_LENGTH = 4;
static const int MAX_EXPECTED_LENGTH = 30;
// Expected distance is about 0.2 ~ 2.0, but consider 0.0 ~ 2.0
static const float MIN_EXPECTED_DISTANCE = 0.0;
static const float MAX_EXPECTED_DISTANCE = 2.0;
// This is not strict: it's where most stuff will be falling, but it's still fine if it's
// outside these values. We want to output a value that reflects all of these. Each factor
// contributes a bit.
// We need at least a space.
if (spaceCount < 1) return NOT_A_FIRST_WORD_CONFIDENCE;
// The smaller the edit distance, the higher the contribution. MIN_EXPECTED_DISTANCE means 0
// contribution, while MAX_EXPECTED_DISTANCE means full contribution according to the
// weight of the distance. Clamp to avoid overflows.
const float clampedDistance = distance < MIN_EXPECTED_DISTANCE ? MIN_EXPECTED_DISTANCE
: distance > MAX_EXPECTED_DISTANCE ? MAX_EXPECTED_DISTANCE : distance;
const int distanceContribution = DISTANCE_WEIGHT_FOR_AUTO_COMMIT
* (MAX_EXPECTED_DISTANCE - clampedDistance)
/ (MAX_EXPECTED_DISTANCE - MIN_EXPECTED_DISTANCE);
// The larger the suggestion length, the larger the contribution. MIN_EXPECTED_LENGTH is no
// contribution, MAX_EXPECTED_LENGTH is full contribution according to the weight of the
// length. Length is guaranteed to be between 1 and 48, so we don't need to clamp.
const int lengthContribution = LENGTH_WEIGHT_FOR_AUTO_COMMIT
* (length - MIN_EXPECTED_LENGTH) / (MAX_EXPECTED_LENGTH - MIN_EXPECTED_LENGTH);
// The more spaces, the larger the contribution. MIN_EXPECTED_SPACE_COUNT space is no
// contribution, MAX_EXPECTED_SPACE_COUNT spaces is full contribution according to the
// weight of the space count.
const int spaceContribution = SPACE_COUNT_WEIGHT_FOR_AUTO_COMMIT
* (spaceCount - MIN_EXPECTED_SPACE_COUNT)
/ (MAX_EXPECTED_SPACE_COUNT - MIN_EXPECTED_SPACE_COUNT);
return distanceContribution + lengthContribution + spaceContribution;
}
/* static */ int SuggestionsOutputUtils::outputShortcuts(
BinaryDictionaryShortcutIterator *const shortcutIt,
int outputWordIndex, const int finalScore, int *const outputCodePoints,
int *const frequencies, int *const outputTypes, const bool sameAsTyped) {
int shortcutTarget[MAX_WORD_LENGTH];
while (shortcutIt->hasNextShortcutTarget() && outputWordIndex < MAX_RESULTS) {
bool isWhilelist;
int shortcutTargetStringLength;
shortcutIt->nextShortcutTarget(MAX_WORD_LENGTH, shortcutTarget,
&shortcutTargetStringLength, &isWhilelist);
int shortcutScore;
int kind;
if (isWhilelist && sameAsTyped) {
shortcutScore = S_INT_MAX;
kind = Dictionary::KIND_WHITELIST;
} else {
// shortcut entry's score == its base entry's score - 1
shortcutScore = finalScore;
// Protection against int underflow
shortcutScore = max(S_INT_MIN + 1, shortcutScore) - 1;
kind = Dictionary::KIND_SHORTCUT;
}
outputTypes[outputWordIndex] = kind;
frequencies[outputWordIndex] = shortcutScore;
frequencies[outputWordIndex] = max(S_INT_MIN + 1, shortcutScore) - 1;
const int startIndex2 = outputWordIndex * MAX_WORD_LENGTH;
DicNodeUtils::appendTwoWords(0, 0, shortcutTarget, shortcutTargetStringLength,
&outputCodePoints[startIndex2]);
++outputWordIndex;
}
return outputWordIndex;
}
} // namespace latinime

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@ -0,0 +1,52 @@
/*
* Copyright (C) 2013 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef LATINIME_SUGGESTIONS_OUTPUT_UTILS
#define LATINIME_SUGGESTIONS_OUTPUT_UTILS
#include "defines.h"
namespace latinime {
class BinaryDictionaryShortcutIterator;
class DicNode;
class DicTraverseSession;
class Scoring;
class SuggestionsOutputUtils {
public:
/**
* Outputs the final list of suggestions (i.e., terminal nodes).
*/
static int outputSuggestions(const Scoring *const scoringPolicy,
DicTraverseSession *traverseSession, int *frequencies, int *outputCodePoints,
int *outputIndicesToPartialCommit, int *outputTypes,
int *outputAutoCommitFirstWordConfidence);
private:
DISALLOW_IMPLICIT_CONSTRUCTORS(SuggestionsOutputUtils);
// Inputs longer than this will autocorrect if the suggestion is multi-word
static const int MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT;
static int computeFirstWordConfidence(const DicNode *const terminalDicNode);
static int outputShortcuts(BinaryDictionaryShortcutIterator *const shortcutIt,
int outputWordIndex, const int finalScore, int *const outputCodePoints,
int *const frequencies, int *const outputTypes, const bool sameAsTyped);
};
} // namespace latinime
#endif // LATINIME_SUGGESTIONS_OUTPUT_UTILS

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@ -19,13 +19,11 @@
#include "suggest/core/dicnode/dic_node.h"
#include "suggest/core/dicnode/dic_node_priority_queue.h"
#include "suggest/core/dicnode/dic_node_vector.h"
#include "suggest/core/dictionary/binary_dictionary_shortcut_iterator.h"
#include "suggest/core/dictionary/dictionary.h"
#include "suggest/core/dictionary/digraph_utils.h"
#include "suggest/core/dictionary/shortcut_utils.h"
#include "suggest/core/dictionary/suggestions_output_utils.h"
#include "suggest/core/layout/proximity_info.h"
#include "suggest/core/policy/dictionary_structure_with_buffer_policy.h"
#include "suggest/core/policy/scoring.h"
#include "suggest/core/policy/traversal.h"
#include "suggest/core/policy/weighting.h"
#include "suggest/core/session/dic_traverse_session.h"
@ -33,9 +31,7 @@
namespace latinime {
// Initialization of class constants.
const int Suggest::MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT = 16;
const int Suggest::MIN_CONTINUOUS_SUGGESTION_INPUT_SIZE = 2;
const float Suggest::AUTOCORRECT_CLASSIFICATION_THRESHOLD = 0.33f;
/**
* Returns a set of suggestions for the given input touch points. The commitPoint argument indicates
@ -70,8 +66,8 @@ int Suggest::getSuggestions(ProximityInfo *pInfo, void *traverseSession,
}
PROF_END(1);
PROF_START(2);
const int size = outputSuggestions(tSession, frequencies, outWords, outputIndices, outputTypes,
outputAutoCommitFirstWordConfidence);
const int size = SuggestionsOutputUtils::outputSuggestions(SCORING, tSession, frequencies,
outWords, outputIndices, outputTypes, outputAutoCommitFirstWordConfidence);
PROF_END(2);
PROF_CLOSE;
return size;
@ -114,205 +110,6 @@ void Suggest::initializeSearch(DicTraverseSession *traverseSession, int commitPo
}
}
/**
* Outputs the final list of suggestions (i.e., terminal nodes).
*/
int Suggest::outputSuggestions(DicTraverseSession *traverseSession, int *frequencies,
int *outputCodePoints, int *outputIndicesToPartialCommit, int *outputTypes,
int *outputAutoCommitFirstWordConfidence) const {
#if DEBUG_EVALUATE_MOST_PROBABLE_STRING
const int terminalSize = 0;
#else
const int terminalSize = min(MAX_RESULTS,
static_cast<int>(traverseSession->getDicTraverseCache()->terminalSize()));
#endif
DicNode terminals[MAX_RESULTS]; // Avoiding non-POD variable length array
for (int index = terminalSize - 1; index >= 0; --index) {
traverseSession->getDicTraverseCache()->popTerminal(&terminals[index]);
}
const float languageWeight = SCORING->getAdjustedLanguageWeight(
traverseSession, terminals, terminalSize);
int outputWordIndex = 0;
// Insert most probable word at index == 0 as long as there is one terminal at least
const bool hasMostProbableString =
SCORING->getMostProbableString(traverseSession, terminalSize, languageWeight,
&outputCodePoints[0], &outputTypes[0], &frequencies[0]);
if (hasMostProbableString) {
outputIndicesToPartialCommit[outputWordIndex] = NOT_AN_INDEX;
++outputWordIndex;
}
// Initial value of the loop index for terminal nodes (words)
int doubleLetterTerminalIndex = -1;
DoubleLetterLevel doubleLetterLevel = NOT_A_DOUBLE_LETTER;
SCORING->searchWordWithDoubleLetter(terminals, terminalSize,
&doubleLetterTerminalIndex, &doubleLetterLevel);
int maxScore = S_INT_MIN;
// Force autocorrection for obvious long multi-word suggestions when the top suggestion is
// a long multiple words suggestion.
// TODO: Implement a smarter auto-commit method for handling multi-word suggestions.
// traverseSession->isPartiallyCommited() always returns false because we never auto partial
// commit for now.
const bool forceCommitMultiWords = (terminalSize > 0) ?
SCORING->autoCorrectsToMultiWordSuggestionIfTop()
&& (traverseSession->isPartiallyCommited()
|| (traverseSession->getInputSize()
>= MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT
&& terminals[0].hasMultipleWords())) : false;
// TODO: have partial commit work even with multiple pointers.
const bool outputSecondWordFirstLetterInputIndex =
traverseSession->isOnlyOnePointerUsed(0 /* pointerId */);
if (terminalSize > 0) {
// If we have no suggestions, don't write this
outputAutoCommitFirstWordConfidence[0] =
computeFirstWordConfidence(&terminals[0]);
}
// Output suggestion results here
for (int terminalIndex = 0; terminalIndex < terminalSize && outputWordIndex < MAX_RESULTS;
++terminalIndex) {
DicNode *terminalDicNode = &terminals[terminalIndex];
if (DEBUG_GEO_FULL) {
terminalDicNode->dump("OUT:");
}
const float doubleLetterCost = SCORING->getDoubleLetterDemotionDistanceCost(
terminalIndex, doubleLetterTerminalIndex, doubleLetterLevel);
const float compoundDistance = terminalDicNode->getCompoundDistance(languageWeight)
+ doubleLetterCost;
const bool isPossiblyOffensiveWord =
traverseSession->getDictionaryStructurePolicy()->getProbability(
terminalDicNode->getProbability(), NOT_A_PROBABILITY) <= 0;
const bool isExactMatch = terminalDicNode->isExactMatch();
const bool isFirstCharUppercase = terminalDicNode->isFirstCharUppercase();
// Heuristic: We exclude freq=0 first-char-uppercase words from exact match.
// (e.g. "AMD" and "and")
const bool isSafeExactMatch = isExactMatch
&& !(isPossiblyOffensiveWord && isFirstCharUppercase);
const int outputTypeFlags =
(isPossiblyOffensiveWord ? Dictionary::KIND_FLAG_POSSIBLY_OFFENSIVE : 0)
| (isSafeExactMatch ? Dictionary::KIND_FLAG_EXACT_MATCH : 0);
// Entries that are blacklisted or do not represent a word should not be output.
const bool isValidWord = !terminalDicNode->isBlacklistedOrNotAWord();
// Increase output score of top typing suggestion to ensure autocorrection.
// TODO: Better integration with java side autocorrection logic.
const int finalScore = SCORING->calculateFinalScore(
compoundDistance, traverseSession->getInputSize(),
terminalDicNode->isExactMatch()
|| (forceCommitMultiWords && terminalDicNode->hasMultipleWords())
|| (isValidWord && SCORING->doesAutoCorrectValidWord()));
if (maxScore < finalScore && isValidWord) {
maxScore = finalScore;
}
// Don't output invalid words. However, we still need to submit their shortcuts if any.
if (isValidWord) {
outputTypes[outputWordIndex] = Dictionary::KIND_CORRECTION | outputTypeFlags;
frequencies[outputWordIndex] = finalScore;
if (outputSecondWordFirstLetterInputIndex) {
outputIndicesToPartialCommit[outputWordIndex] =
terminalDicNode->getSecondWordFirstInputIndex(
traverseSession->getProximityInfoState(0));
} else {
outputIndicesToPartialCommit[outputWordIndex] = NOT_AN_INDEX;
}
// Populate the outputChars array with the suggested word.
const int startIndex = outputWordIndex * MAX_WORD_LENGTH;
terminalDicNode->outputResult(&outputCodePoints[startIndex]);
++outputWordIndex;
}
if (!terminalDicNode->hasMultipleWords()) {
BinaryDictionaryShortcutIterator shortcutIt(
traverseSession->getDictionaryStructurePolicy()->getShortcutsStructurePolicy(),
traverseSession->getDictionaryStructurePolicy()
->getShortcutPositionOfPtNode(terminalDicNode->getPtNodePos()));
// Shortcut is not supported for multiple words suggestions.
// TODO: Check shortcuts during traversal for multiple words suggestions.
const bool sameAsTyped = SCORING->sameAsTyped(traverseSession, terminalDicNode);
const int shortcutBaseScore = SCORING->doesAutoCorrectValidWord() ?
SCORING->calculateFinalScore(compoundDistance, traverseSession->getInputSize(),
true /* forceCommit */) : finalScore;
const int updatedOutputWordIndex = ShortcutUtils::outputShortcuts(&shortcutIt,
outputWordIndex, shortcutBaseScore, outputCodePoints, frequencies, outputTypes,
sameAsTyped);
const int secondWordFirstInputIndex = terminalDicNode->getSecondWordFirstInputIndex(
traverseSession->getProximityInfoState(0));
for (int i = outputWordIndex; i < updatedOutputWordIndex; ++i) {
if (outputSecondWordFirstLetterInputIndex) {
outputIndicesToPartialCommit[i] = secondWordFirstInputIndex;
} else {
outputIndicesToPartialCommit[i] = NOT_AN_INDEX;
}
}
outputWordIndex = updatedOutputWordIndex;
}
DicNode::managedDelete(terminalDicNode);
}
if (hasMostProbableString) {
SCORING->safetyNetForMostProbableString(terminalSize, maxScore,
&outputCodePoints[0], &frequencies[0]);
}
return outputWordIndex;
}
int Suggest::computeFirstWordConfidence(const DicNode *const terminalDicNode) const {
// Get the number of spaces in the first suggestion
const int spaceCount = terminalDicNode->getTotalNodeSpaceCount();
// Get the number of characters in the first suggestion
const int length = terminalDicNode->getTotalNodeCodePointCount();
// Get the distance for the first word of the suggestion
const float distance = terminalDicNode->getNormalizedCompoundDistanceAfterFirstWord();
// Arbitrarily, we give a score whose useful values range from 0 to 1,000,000.
// 1,000,000 will be the cutoff to auto-commit. It's fine if the number is under 0 or
// above 1,000,000 : under 0 just means it's very bad to commit, and above 1,000,000 means
// we are very confident.
// Expected space count is 1 ~ 5
static const int MIN_EXPECTED_SPACE_COUNT = 1;
static const int MAX_EXPECTED_SPACE_COUNT = 5;
// Expected length is about 4 ~ 30
static const int MIN_EXPECTED_LENGTH = 4;
static const int MAX_EXPECTED_LENGTH = 30;
// Expected distance is about 0.2 ~ 2.0, but consider 0.0 ~ 2.0
static const float MIN_EXPECTED_DISTANCE = 0.0;
static const float MAX_EXPECTED_DISTANCE = 2.0;
// This is not strict: it's where most stuff will be falling, but it's still fine if it's
// outside these values. We want to output a value that reflects all of these. Each factor
// contributes a bit.
// We need at least a space.
if (spaceCount < 1) return NOT_A_FIRST_WORD_CONFIDENCE;
// The smaller the edit distance, the higher the contribution. MIN_EXPECTED_DISTANCE means 0
// contribution, while MAX_EXPECTED_DISTANCE means full contribution according to the
// weight of the distance. Clamp to avoid overflows.
const float clampedDistance = distance < MIN_EXPECTED_DISTANCE ? MIN_EXPECTED_DISTANCE
: distance > MAX_EXPECTED_DISTANCE ? MAX_EXPECTED_DISTANCE : distance;
const int distanceContribution = DISTANCE_WEIGHT_FOR_AUTO_COMMIT
* (MAX_EXPECTED_DISTANCE - clampedDistance)
/ (MAX_EXPECTED_DISTANCE - MIN_EXPECTED_DISTANCE);
// The larger the suggestion length, the larger the contribution. MIN_EXPECTED_LENGTH is no
// contribution, MAX_EXPECTED_LENGTH is full contribution according to the weight of the
// length. Length is guaranteed to be between 1 and 48, so we don't need to clamp.
const int lengthContribution = LENGTH_WEIGHT_FOR_AUTO_COMMIT
* (length - MIN_EXPECTED_LENGTH) / (MAX_EXPECTED_LENGTH - MIN_EXPECTED_LENGTH);
// The more spaces, the larger the contribution. MIN_EXPECTED_SPACE_COUNT space is no
// contribution, MAX_EXPECTED_SPACE_COUNT spaces is full contribution according to the
// weight of the space count.
const int spaceContribution = SPACE_COUNT_WEIGHT_FOR_AUTO_COMMIT
* (spaceCount - MIN_EXPECTED_SPACE_COUNT)
/ (MAX_EXPECTED_SPACE_COUNT - MIN_EXPECTED_SPACE_COUNT);
return distanceContribution + lengthContribution + spaceContribution;
}
/**
* Expands the dicNodes in the current search priority queue by advancing to the possible child
* nodes based on the next touch point(s) (or no touch points for lookahead)

View file

@ -55,18 +55,11 @@ class Suggest : public SuggestInterface {
DISALLOW_IMPLICIT_CONSTRUCTORS(Suggest);
void createNextWordDicNode(DicTraverseSession *traverseSession, DicNode *dicNode,
const bool spaceSubstitution) const;
int outputSuggestions(DicTraverseSession *traverseSession, int *frequencies,
int *outputCodePoints, int *outputIndicesToPartialCommit, int *outputTypes,
int *outputAutoCommitFirstWordConfidence) const;
int computeFirstWordConfidence(const DicNode *const terminalDicNode) const;
void initializeSearch(DicTraverseSession *traverseSession, int commitPoint) const;
void expandCurrentDicNodes(DicTraverseSession *traverseSession) const;
void processTerminalDicNode(DicTraverseSession *traverseSession, DicNode *dicNode) const;
void processExpandedDicNode(DicTraverseSession *traverseSession, DicNode *dicNode) const;
void weightChildNode(DicTraverseSession *traverseSession, DicNode *dicNode) const;
float getAutocorrectScore(DicTraverseSession *traverseSession, DicNode *dicNode) const;
void generateFeatures(
DicTraverseSession *traverseSession, DicNode *dicNode, float *features) const;
void processDicNodeAsOmission(DicTraverseSession *traverseSession, DicNode *dicNode) const;
void processDicNodeAsDigraph(DicTraverseSession *traverseSession, DicNode *dicNode) const;
void processDicNodeAsTransposition(DicTraverseSession *traverseSession,
@ -79,13 +72,8 @@ class Suggest : public SuggestInterface {
void processDicNodeAsMatch(DicTraverseSession *traverseSession,
DicNode *childDicNode) const;
// Inputs longer than this will autocorrect if the suggestion is multi-word
static const int MIN_LEN_FOR_MULTI_WORD_AUTOCORRECT;
static const int MIN_CONTINUOUS_SUGGESTION_INPUT_SIZE;
// Threshold for autocorrection classifier
static const float AUTOCORRECT_CLASSIFICATION_THRESHOLD;
const Traversal *const TRAVERSAL;
const Scoring *const SCORING;
const Weighting *const WEIGHTING;